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In case a metric shows that the action taken is not beneficial, a different approach can be taken to fulfill the needs of a target.

A good performance metrics yields outcomes that measure the quantities for improvement to an overall organisational goal. Measuring performance may result as the key to gain the targets in an organisation. It is important for a data scientist to assess the particular process that needs amendments to execute the result of a model. This involves working on the process of improvement opportunities. The result gained from analysis is used to guide the operational workers and managers in order to solve the issues in any organisation. The model is built to identify problems of an organisation. It is very crucial to define the goals based on the objectives. There are several objectives such as risk and fraud management, forecast revenue, financial modelling, social media influencers, manage marketing campaigns, operational efficiency and many more, the only thing is we need to choose accordingly. One should have a clear objective for building a predictive analysis model.

In this article, we list simple steps that can help you to understand and build a successful predictive analysis model. Predictive analysis model helps in improving the effectiveness of an organisation and driving successful outcome in an enterprise with the help of data, statistics, and machine learning techniques.